41 citations · 75 across the 6 of their papers we have counts for
6 papers
When Diffusion Breaks Constraints: Sequential Autoregressive Generation with RL and MCTS
Zirui Zhao, Boye Niu, Harold Soh +2
Data-driven generative models excel in language and vision, but diffusion models often fail in constrained planning and design tasks, exhibiting severe constraint violations in eng…
On the Empirical Complexity of Reasoning and Planning in LLMs
Liwei Kang, Zirui Zhao, David Hsu +1
Chain-of-thought (CoT), tree-of-thought (ToT), and related techniques work surprisingly well in practice for some complex reasoning tasks with Large Language Models (LLMs), but why…
Large Language Models as Commonsense Knowledge for Large-Scale Task Planning
Zirui Zhao, Wee Sun Lee, David Hsu
Large-scale task planning is a major challenge. Recent work exploits large language models (LLMs) directly as a policy and shows surprisingly interesting results. This paper shows…
Differentiable Parsing and Visual Grounding of Natural Language Instructions for Object Placement
Zirui Zhao, Wee Sun Lee, David Hsu
We present a new method, PARsing And visual GrOuNding (ParaGon), for grounding natural language in object placement tasks. Natural language generally describes objects and spatial…
Visual Semantic SLAM with Landmarks for Large-Scale Outdoor Environment
Zirui Zhao, Yijun Mao, Yan Ding +2
Semantic SLAM is an important field in autonomous driving and intelligent agents, which can enable robots to achieve high-level navigation tasks, obtain simple cognition or reasoni…
Active Learning for Risk-Sensitive Inverse Reinforcement Learning
Rui Chen, Wenshuo Wang, Zirui Zhao +1
One typical assumption in inverse reinforcement learning (IRL) is that human experts act to optimize the expected utility of a stochastic cost with a fixed distribution. This assum…